BACKGROUND: Vaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other subject-specific characteristics evaluated as baseline covariates. Understanding the effect of covariates on efficacy is key to decisions by vaccine developers and public health authorities. METHODS: This work evaluates the impact of including correlate of protection (CoP) data in logistic regression on its performance in identifying statistically and clinically significant covariates in settings typical for a vaccine phase 3 trial. The proposed approach uses CoP data and covariate data as predictors of clinical outcome (diseased versus non-diseased) and is compared to logistic regression (without CoP data) to relate vaccination status and covariate data to clinical outcome. RESULTS: Clinical trial simulations, in which the true relationship between CoP data and clinical outcome probability is a sigmoid function, show that use of CoP data increases the positive predictive value for detection of a covariate effect. If the true relationship is characterized by a decreasing convex function, use of CoP data does not substantially change positive or negative predictive value. In either scenario, vaccine efficacy is estimated more precisely (i.e., confidence intervals are narrower) in covariate-defined subgroups if CoP data are used, implying that using CoP data increases the ability to determine clinical significance of baseline covariate effects on efficacy. CONCLUSIONS: This study proposes and evaluates a novel approach for assessing baseline demographic covariates potentially affecting VE. Results show that the proposed approach can sensitively and specifically identify potentially important covariates and provides a method for evaluating their likely clinical significance in terms of predicted impact on vaccine efficacy. It shows further that inclusion of CoP data can enable more precise VE estimation, thus enhancing study power and/or efficiency and providing even better information to support health policy and development decisions.

• Keywords
• Baseline covariates, Correlate of protection, Logistic regression, Relative risk, Vaccine efficacy,
• MeSH
• Demography statistics & numerical data   MeSH
• Clinical Trials, Phase III as Topic statistics & numerical data   methods   MeSH
• Humans MeSH
• Logistic Models MeSH
• Computer Simulation MeSH
• Randomized Controlled Trials as Topic statistics & numerical data   methods   MeSH
• Vaccine Efficacy * statistics & numerical data   MeSH
• Vaccination statistics & numerical data   methods   MeSH
• Vaccines therapeutic use   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Vaccines MeSH

The importance of environmental sustainability is becoming more and more obvious, so the rationale behind long-term usage of solely non-renewable energy sources appeared questionable. This study aims to identify, using Kaplan-Meier survival analysis and logistic regressions, the main determinants that affect the duration of Russian non-renewable energy exports to different regions of the world. Data were retrieved from the databanks of the World Development Indicators (WDI), World Integrated Trade Solution (WITS), and the French Centre for Prospective studies and International Information (CEPII). The obtained results point to the fact that approximately 52% of energy products survive beyond their first year of trading, nearly 38% survive beyond the second year, and almost 18% survive to the twelfth year. The survival of Russian non-renewable energy exports differs depending on the region, and the affecting factors are of different importance. The duration of Russian non-renewable energy exports is significantly linked to Russia's GDP, Total export, and Initial export values. A decline in Russia's GDP by 1% is associated with an increasing probability of a spell ending by 2.9% on average, in turn growing Total export and Initial export values positively linked with the duration of non-renewable energy exports from Russia. These findings may have practical relevance for strategic actions aimed at approaching both energy security and environmental sustainability.

• Keywords
• Russia, discrete-time model, environmental sustainability, non-renewable energy exports, survival analysis,
• MeSH
• Economic Development * MeSH
• Logistic Models MeSH
• Carbon Dioxide * MeSH
• Prospective Studies MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Russia MeSH
• Names of Substances
• Carbon Dioxide * MeSH

At the beginning of 2020 there was a spinning point in the travel behavior of people around the world because of the pandemic and its consequences. This paper analyzes the specific behavior of travelers commuting to work or school during the COVID-19 pandemic based on a sample of 2000 respondents from two countries. We obtained data from an online survey, applying multinomial regression analysis. The results demonstrate the multinomial model with an accuracy of almost 70% that estimates the most used modes of transport (walking, public transport, car) based on independent variables. The respondents preferred the car as the most frequently used means of transport. However, commuters without car prefer public transport to walking. This prediction model could be a tool for planning and creating transport policy, especially in exceptional cases such as the limitation of public transport activities. Therefore, predicting travel behavior is essential for policymaking based on people's travel needs.

• Keywords
• COVID-19, mobility, multinomial regression model, transport,
• MeSH
• COVID-19 * MeSH
• Bicycling MeSH
• Transportation MeSH
• Humans MeSH
• Logistic Models MeSH
• Pandemics * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Classifying a measurable clinical outcome as a dichotomous variable often involves difficulty with borderline cases that could fairly be assigned either of the two binary class memberships. In such situations the indicated class membership is often highly subjective and subject to, for instance, a measurement error. In other situations the intermediate level of a three-level ordinal factor may sometimes be explicitly reserved for cases which could likely belong to either of the two binary classes. Such indefinite readings are often eliminated from the statistical analysis. In this article we review conceptual and methodological aspects of employing proportional odds logistic regression for a three level ordinal factor as a suitable alternative to ordinary logistic regression when dealing with limited uncertainty in classifying clinical outcome as a binary variable.

• MeSH
• Atherosclerosis diagnostic imaging   MeSH
• Cholesterol blood   MeSH
• Data Interpretation, Statistical * MeSH
• Smoking MeSH
• Blood Glucose metabolism   MeSH
• Humans MeSH
• Logistic Models * MeSH
• Predictive Value of Tests MeSH
• Models, Statistical * MeSH
• Ultrasonography MeSH
• Calcium blood   MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic MeSH
• Names of Substances
• Cholesterol MeSH
• Blood Glucose MeSH
• Calcium MeSH

Accuracy of identification tools in forensic anthropology primarily rely upon the variations inherent in the data upon which they are built. Sex determination methods based on craniometrics are widely used and known to be specific to several factors (e.g. sample distribution, population, age, secular trends, measurement technique, etc.). The goal of this study is to discuss the potential variations linked to the statistical treatment of the data. Traditional craniometrics of four samples extracted from documented osteological collections (from Portugal, France, the U.S.A., and Thailand) were used to test three different classification methods: linear discriminant analysis (LDA), logistic regression (LR), and support vector machines (SVM). The Portuguese sample was set as a training model on which the other samples were applied in order to assess the validity and reliability of the different models. The tests were performed using different parameters: some included the selection of the best predictors; some included a strict decision threshold (sex assessed only if the related posterior probability was high, including the notion of indeterminate result); and some used an unbalanced sex-ratio. Results indicated that LR tends to perform slightly better than the other techniques and offers a better selection of predictors. Also, the use of a decision threshold (i.e. p>0.95) is essential to ensure an acceptable reliability of sex determination methods based on craniometrics. Although the Portuguese, French, and American samples share a similar sexual dimorphism, application of Western models on the Thai sample (that displayed a lower degree of dimorphism) was unsuccessful.

• Keywords
• Accuracy, Forensic anthropology population data, Population, Reliability, Sex estimation, Statistics,
• MeSH
• Discriminant Analysis MeSH
• Cephalometry * MeSH
• Humans MeSH
• Logistic Models MeSH
• Racial Groups MeSH
• Reproducibility of Results MeSH
• Forensic Anthropology MeSH
• Support Vector Machine MeSH
• Sex Determination by Skeleton methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Comparative Study MeSH

The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based features. In total, one-hundred and sixty rainbow trout (Oncorhynchus mykiss) were fed either a fish-meal based diet (80 fish) or a 100% plant-based diet (80 fish) and photographed using consumer-grade digital camera. Twenty-three colour features and four texture features were extracted. Four different classification methods were used to evaluate fish diets including Random forest (RF), Support vector machine (SVM), Logistic regression (LR) and k-Nearest neighbours (k-NN). The SVM with radial based kernel provided the best classifier with correct classification rate (CCR) of 82% and Kappa coefficient of 0.65. Although the both LR and RF methods were less accurate than SVM, they achieved good classification with CCR 75% and 70% respectively. The k-NN was the least accurate (40%) classification model. Overall, it can be concluded that consumer-grade digital cameras could be employed as the fast, accurate and non-invasive sensor for classifying rainbow trout based on their diets. Furthermore, these was a close association between image-based features and fish diet received during cultivation. These procedures can be used as non-invasive, accurate and precise approaches for monitoring fish status during the cultivation by evaluating diet's effects on fish skin.

• Keywords
• image colour properties, image processing, image texture properties, machine vision system, supervised classification,
• MeSH
• Diet MeSH
• Logistic Models MeSH
• Oncorhynchus mykiss MeSH
• Support Vector Machine * MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Comparative Study MeSH

A set of 69 concentration-response curves from 5 acute ecotoxicity assays was fitted with a 2-parameter logistic equation. High correlation between values of regression parameters suggested similar slopes of the curves. This enabled derivation of the empirical single-parameter logistic equation with the sole median effective concentration (EC50) parameter. Such an equation might be useful in the evaluation of lower-quality (preliminary) experimental data and for the reduction of the number of test organisms and of testing costs.

• Keywords
• Acute ecotoxicity assays, Concentration-response slope, EC50 calculation, Logistic model,
• MeSH
• Aliivibrio fischeri drug effects   MeSH
• Chlorophyta drug effects   MeSH
• Daphnia drug effects   MeSH
• Potassium Dichromate toxicity   MeSH
• Environmental Pollutants toxicity   MeSH
• Logistic Models * MeSH
• Reference Standards MeSH
• Toxicity Tests, Acute * standards   MeSH
• Poecilia MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Potassium Dichromate MeSH
• Environmental Pollutants MeSH

In the present paper the prediction method using the logistic regression is explained, and the range of problems for its use is deliminated. The example is presented of mentioned method's application on how to predict the dog survival in a radiolobiological experiment. The obtained results are compared with the prediction of outcome using the linear discriminant function. Both models are identic in a proportion of erroneously classified subjects. This method may be diagnostically supportive in ranging individuals to one of two groups delimitated previously.

• MeSH
• Regression Analysis * MeSH
• Publication type
• English Abstract MeSH
• Journal Article MeSH

OBJECTIVES: This study aims at proposing a visual method for sexing the human os coxae based on a statistical approach, using a scoring system of traits described by Bruzek (2002). This method is evaluated on a meta-population sample, where the data were acquired by direct observation of dry bones as well as computed tomography (CT) scans. A comparison with the original Bruzek's (2002) method is performed. MATERIALS AND METHODS: Five hundred and ninety two ossa coxae of modern humans are included in the reference dataset. Two other samples, composed respectively of 518 ossa coxae and 99 CT-scan images, are both used for validation purposes. The individuals come from five European or North American population samples. Eleven trichotomic traits (expressing female, male, or intermediate forms) were observed on each os coxae. The new approach employs statistical processing based on logistic regressions. An R package freely available online, PELVIS, implements both methods. RESULTS: Both methods provide highly reliable sex estimates. The new statistical method has a slightly better accuracy rate (99.2%) than the former method (98.2%) but has also a higher rate of indeterminate individuals (12.9% vs. 3% for complete bones). CONCLUSION: The efficiency of both methods is compared. Low error rates were preferred over high ability of reaching the classification threshold. The impact of lateralization and the asymmetry of observed traits are discussed. Finally, it is shown that this visual method of sex estimation is reliable and easy to use through the graphical user interface of the R package.

• Keywords
• hip bone, identification, innominate, morphoscopy, sex estimation,
• MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Logistic Models * MeSH
• Young Adult MeSH
• Pelvic Bones anatomy & histology   MeSH
• Tomography, X-Ray Computed MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Forensic Anthropology methods   MeSH
• Sex Determination by Skeleton methods   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Estrogenic compounds as well as other biologically active substances are commonly present in the form of complex mixtures in the environment. There is still no satisfactory model that would be capable of predicting the toxic effects of mixtures containing partial receptor agonists and compounds with different parameters of their dose-response curves. Therefore, a novel Full Logistic Model (FLM) of prediction using all the parameters of dose-response curves has been suggested and compared with previously published approaches. We tested the receptor-binding activities of selected estrogens including full and partial agonists and their mixtures using yeast reporter gene assays and the human T47D cell line. Combination effects were modeled with FLM and predicted curves were compared with the data obtained experimentally. FLM yielded a good fit to the experimental data from both the receptor-binding assays and gave better predictions than the previously published approaches. FLM also provided satisfactory results regarding final partial agonistic dose-response curves with maximum influenced by the inhibitory effect of the partial agonist. FLM is not limited by any simplification like the toxic equivalency factor approach or generalized concentration addition and therefore it could be employed for mixtures containing chemicals with different parameters of their dose-response curves (maximum, minimum, inflex point or slope).

• Keywords
• Additive effect, Concentration addition, Endocrine disrupting compounds, Estrogen receptor, Logistic curve, T47D,
• MeSH
• Benzhydryl Compounds pharmacology   MeSH
• Biological Assay MeSH
• Cell Line MeSH
• Chemokine CXCL12 metabolism   MeSH
• Estradiol pharmacology   MeSH
• Estrogens pharmacology   MeSH
• Phenols pharmacology   MeSH
• Drug Interactions MeSH
• Humans MeSH
• Logistic Models * MeSH
• Genes, Reporter MeSH
• Saccharomyces cerevisiae genetics   MeSH
• Dose-Response Relationship, Drug MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Benzhydryl Compounds MeSH
• bisphenol A MeSH Browser
• Chemokine CXCL12 MeSH
• CXCL12 protein, human MeSH Browser
• Estradiol MeSH
• Estrogens MeSH
• Phenols MeSH